on the predictive power of the term structure of interest rates for future inflation changes in the...

Journal of Policy Modeling25 (2003) 931–946

On the predictive power of the term structureof interest rates for future inflation changes

in the presence of political instability:the Turkish economy

Erdinc Telatara,∗, Funda Telatarb, Ronald A. Rattic

aDepartment of Economics, Hacettepe University, Beytepe, Ankara, TurkeybDepartment of Economics, Gazi University, Turkey

cDepartment of Economics, University of Missouri-Columbia, MO, USA

Received 1 February 2002; accepted 1 August 2003

Abstract

This study investigates whether the term structure contains useful information about fu-ture inflation for Turkey during 1990–2000, a period of high inflation, high budget deficits,and political instability. Constant parameter and time varying parameter models are rejectedby the data. The relationship between term structure of interest rates and inflation changesis found to be explained by a time-varying-parameter model with Markov-switching het-eroskedastic disturbances. Thus, the term structure of interest rates is limited as a guide formonetary policy in an economy subject to regime changes such as that of Turkey. Stabilitycan be achieved only by reducing inflation through circumscribing substantial governmentbudget deficits and the political instability underlying them.© 2003 Society for Policy Modeling. Published by Elsevier Inc. All rights reserved.

JEL classification: E4; G0

Keywords: Term structure of interest rates; Monetary policy; Markov-switch model; Inflation

∗ Corresponding author.E-mail addresses: [email protected] (E. Telatar), [email protected] (F. Telatar), Rat-

[email protected] (R.A. Ratti).

0161-8938/$ – see front matter © 2003 Society for Policy Modeling.doi:10.1016/j.jpolmod.2003.08.003

932 E. Telatar et al. / Journal of Policy Modeling 25 (2003) 931–946

1. Introduction

Much recent research on the term structure of interest rates has been focused ondetermining the information content in the term structure of interest rates. In hisseminal paper,Fama (1975)found that changes in nominal interest rates reflect fluc-tuations in expected inflation rather than the changes in real interest rates, and thatconsequently nominal interest rates can be used as an predictor of future inflation.Numerous studies have been conducted to test the validity of Fama’s hypothesis fordeveloped countries. For instance,Nelson and Schwert (1977), Mishkin (1981),andFama and Gibbons (1982)report evidence in support of the Fisher effect forthe United States. On the other hand,Mishkin (1984)offers evidence in favourof rejection of the effect for some OECD countries.1 Another line of research hasfocused on the expectations hypothesis which emphasizes the predictive powerof the term structure for future interest rate movements. Empirical research onthis issue provides evidence that the term structure of interest rates contains use-ful information about future interest rates (i.e.,Campbell & Shiller, 1987; Fama,1984; Mankiw & Summers, 1984). By combining these two lines of research,Mishkin (1990)argues that the term structure might contain information aboutfuture inflation, and therefore can be used as a guide or an information variablefor implementing monetary policy towards the target of ensuring price stability.

Empirical studies on the predictive power of the term structure for futurechanges in inflation have mainly been confined to work on developed countries,particularly for the United States and the European countries.2 Recent studies(Caporale & Pitts, 1998; Gerlach, 1997; Jorion & Mishkin, 1991; Klug & Naval,1999; Mishkin, 1990; Schich, 1999) support Mishkin’s hypothesis. In contrast,Koedijk and Kool (1995)finds no supportive evidence of the hypothesis and em-phasizes that results are both time and country dependent. A common feature ofthese studies is use of fixed-coefficient regression models, based on the assump-tion that there is a stable relation between the term structure of interest rates andchanges in inflation. However, as stated byMishkin (1990), when the relationshipbetween the term structure and inflation is unstable, it would not be possible toprovide correct information about the inflationary pressures in the economy by us-ing the estimated parameters of the linear model, and therefore the term structureof interest rates would no longer be a guide for future monetary policies aimed atensuring price stability. To overcome this problem,Mishkin (1990)andCaporaleand Pitts (1998)impose structural break-points into the model based on changes inthe political environment or in policy regimes, and then estimate a fixed-coefficientmodel within each sub-period.

1 Mishkin (1992)investigates the constancy of real interest rates over the short- and long-run. Hefinds that Fisher effect holds over the long run and that real interest rates are not constant over theshort-run.

2 Gonzalez, Spencer, and Walz (2000)investigate the term structure of interest rates for developingcountries.

E. Telatar et al. / Journal of Policy Modeling 25 (2003) 931–946 933

The objective of this paper is to test hypotheses about the relationship betweenthe term structure of interest rates and future changes in inflation for Turkey overthe period of 1990–2000, using monthly observations on one–six-month govern-ment security interest rates available from the secondary market for governmentsecurities. This is an interesting issue because Turkey is a developing country thathas a number of changes in government, changes in stabilization programs, andexperienced high and variable inflation.3 Many stabilization programs have ad-dressed the problem of high inflation in Turkey over the years, yet all have failedin reducing inflation to acceptable rates.

We find that the relationship between the term structure of interest rates andinflation changes can best be explained with a model that combines time-varyingparameters and Markov-switching heteroskedasticity in the error terms. A fixed-coefficient regression model is rejected by the data even when applied to sub-samples corresponding to specific stabilization programs. Political instability andconsequent frequent change in monetary and fiscal policies and stabilization re-gimes during the sample period make allowance for endogenous parameter changeand Markov-switching in heteroskedasticity in the errors in the estimation an at-tractive model for the Turkish economy. We note that the switching probabilities forthe model with three- and one-month interest rates are highly significant and persis-tent, suggesting regime changes did not appear frequently. Regime change occursat times consistent with dates of exceptional economic and political uncertainty inTurkey. It is likely that economic stability and low inflation can be achieved onlythrough balanced budgets and the development of stable political institutions.4

The next section presents a brief overview of the Turkish economy. InSection3 we outline the inflation-change equation constructed byMishkin (1990)anddevelop a time-varying parameter model with Markov-switching heteroskedasticdisturbances. InSection 3, we also describe the data and discuss empirical results.Section 4is the conclusion.

2. Overview of the Turkish economy

Annual data on macroeconomic indicators of the Turkish economy are presentedin Table 1. The period 1990–2000 is characterized by high and variable inflation.The GNP-deflator averaged increases of 71.2% over the period, with a low value of50.9% in 2000 and a high value of 107.3% in 1994. In line with inflation, the Turkish

3 The relationship between government and institutions in charge of implementing economic poli-cies in Turkey differ from those in the developed countries. The Central Bank of the Republic ofTurkey (CB) is directly or indirectly controlled by government, and could be forced to act in line withgovernmental preferences for monetary and fiscal policy implemented at government direction by theMinistry of Finance.

4 In recent decades it is likely that Turkey provides an example of cases discussed byCukierman,Edwards, and Tabellini (1992)andRodrik (1996)in which government tries to reap short-term benefits,including maintaining hold on power, by reneging on announced reforms that would provide longerterm benefits.

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Table 1Main macroeconomic indicators

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000

Real growth rate 9.4 0.3 6.4 8.1 −6.1 8.0 7.1 8.3 3.9 −6.1 6.3GNP deflator 57.6 59.2 63.5 67.3 107.3 87.2 78.0 81.2 75.3 56.2 50.9PSBR/GNP 7.4 10.2 10.6 12.0 7.9 5.2 8.8 7.7 9.4 15.6 12.5Domestic debt stock (net)/GNP 14.4 15.4 17.6 17.9 20.6 17.3 21.0 21.4 21.7 29.3 29.0Domestic borrowing/domestic debt stock 52.3 67.0 94.4 105.3 128.9 129.4 163.5 99.1 119.8 117.3 89.1Annual average interest rate on

government securities51.7 69.6 75.0 85.3 136.9 107.8 121.9 119.1 99.0 105.3 34.9

Real interest ratea −3.7 6.6 7.1 10.7 14.3 11.1 24.7 20.9 13.5 31.8 −10.6Short-term advances from CB/total

finance of budget deficits (%)2.4 32.1 29.3 42.0 34.1 32.2 18.1

Portfolio investment (million $) 547 623 2411 3917 1158 237 570 1634−6711 3429 1022Growth rate of exchange rate (US$, %) 26.6 73.3 68.6 68.9 167.7 46.3 84.4 90.7 53.8 71.7 28.7Government expenditure (total)/GNP 16.9 20.5 20.1 24.3 23.1 21.8 26.3 27.2 29.2 35.9 37.4Tax revenues/GNP 11.4 12.4 12.8 13.2 15.1 13.8 15.0 16.1 17.2 18.9 21.1Seigniorageb/GNP 4.7 7.1 8.4 6.2 6.8 6.2 5.6 0.6 0.2 2.6 −0.3Short-term capitalc (million $) 3000 −3020 1396 3054 −5127 3713 2737 77 1398 759 4200Fixed capital investments/GNP 22.6 23.7 23.4 26.3 24.5 24.0 25.1 26.3 24.3 22.1 22.6Total financial assets/GNP 32.0 37.0 42.0 40.0 46.0 47.0 58.0 61.0 64.0 86.0 79.0

PSBR: public sector borrowing requirement, GNP: Gross National Product, CB: Central Bank of Republic of Turkey.a Ex post real interest rate is calculated by using Fisher equationr = (i − �)/(1 + �).b Seigniorage is calculated by using the formula ofSrev = m + �m, whereSrev is seigniorage,m is the growth rate of real monetary base,m is the stock of real

monetary base and� is inflation rate.c Short-term capital includes assets (credits extended, bank reserves and other assets) and liabilities (credits received and deposits).


lira has depreciated at a rapid rate over the period with the greatest loss in value rela-tive to the US dollar (168%) occurring in 1994. The growth rate of real GNP has alsofluctuated widely, between−6.1 and 9.4%, with an average value of 4.1% per year.

The main factor behind the inflationary process has been the need to finance highbudget deficits. Although tax revenue relative to GNP has shown an upward trendover 1990–2000, government expenditure relative to GNP hasgrown even faster.The public sector borrowing requirement andseigniorage relative to GNP havebeen high with average values of 9.7 and 4.4%, respectively. The nominal interestrate on one-month government securities, driven by the public sector borrowingrequirement, achieved a high of 137% per annum in 1994. The real interest rateexpost has varied between−10.6 and 31.8%.

Following the approach ofEngle (1983), Fama (1981), andLee and Ni (1996),we performed regression analyses of inflation as a preliminary test to see thedynamics of inflation in Turkish economy. The estimated regression with monthlydata is given by

inflationt = 1.74(0.48)

+ 0.53(0.10)

inflationt−1 + 0.42(0.19)

�interest ratet−1

+0.05(0.02)

�log moneyt−1 + 0.03(0.03)

�log wage ratet−1

+0.09(0.05)

�log import price indext−1′

R2 = .39,F = 10.33, Bruesch–Godfrey, LM= 22.48, LM ARCH (1) = 0.09,standard errors are in parentheses.

The results show that the changes in interest rates, the growth rate of moneysupply, and the exchange rate have played a role in determining the inflation ratein Turkey. The magnitude of the estimated coefficient for the interest rate suggeststhat the public sector borrowing requirement (PSBR) has had major influence onthe determination of inflation.5 Short-term borrowing at high interest rates causeda need for re-borrowing in order to make debt service payments, and created avicious circle of high budgetdeficits and high interest rates. The public sector bor-rowing requirement has been financed either through short-term advances to theTreasury from the Central Bank (CB) or through the sale of government securities.In Table 1it is seen that short-term advances as a fraction of budget deficits aver-aged 27% over 1990–1996. In 1997, a Treasury-CB agreement gave priority to theuse of government securities to finance budget deficits as a means of increasingtransparency in government activity.6

5 Sims (1994), Leeper (1991), andWoodford (1994)have emphasized the role of fiscal policy indetermination of prices.Telatar (2002)provides evidence supportive of the importance of public sectorborrowing requirement in determining the Turkish price level with the method used inCanzoneri,Cumby, and Diba (2001).

6 Unofficially the resources of CB continued to be used indirectly through state-owned banks toconceal financing of the budget deficit. Agencies of government have been prohibited from using CBcredit (direct or indirect) since November 5, 2001.


Table 2Changes in government and stabilization programs, 1990–2002

Prime minister Years Stabilization programs

Akbulut 9 November 1989–23 June 1991 1990 Monetary ProgramI. Yilmaz 23 June 1991–20 November 1991VII. Demirel 21 November 1991–25 June 1993I. Ciller 25 June 1993–5 October 1995 5 April 1994-stabilization programII. Ciller 5 October 1995–30 October 1995III. Ciller 30 October 1995–6 March 1996II. Yilmaz 6 March 1996–28 June 1996Erbakan 28 June 1996–30 June 1997III. Yilmaz 30 June 1997–11 January 1999IV. Ecevit 11 January 1999–28 May 1999V. Ecevit 28 May 1999–3 November 2002 14 April 2001-stabilization program

Along the lines of argument byFriedman (1977), high inflation has been associ-ated with increased uncertainty and the inefficient use of resources. High nominalinterest rates (as emphasized byStiglitz & Weiss, 1992) have compounded moralhazard and adverse selection problems and made the banking sector reluctant toextend new credits to the real sector. During 1990–2000, the banking sector movedaway from financing projects in the private sector and increased the share of gov-ernment securities in total assets from 10% in 1990 to 23% in 1999. High andvolatile inflation rates accelerated currency substitution by private agents as theshare of foreign exchange deposits in total deposits increased from 25% in 1990to 42% in 1999. Increases in borrowing from abroad increased the exchange raterisk of the banking sector.

Economic events over 1990–2000 cannot be understood without reference tothe political environment. Turkey experienced 11 government changes during1990–2000 as shown inTable 2. An underfunded legal system has contributedto pursuit of myopic policies byincumbent politicians described in the literatureon the positive analysis of policy formation.7 Since high and chronic inflation is aconsequence of high budget deficits driven by electoral calculus, it is reasonableto conclude that institutional weakness is a contributing factor to economic insta-bility. Indeed, Turkey seems in recent decades to demonstrate the thesis laid outby Acemoglu, Johnson, Robinson, and Thaicharoen (2003)that greater economicinstability is to be expected in institutionally weak societies.8

The political environment has influenced the need and disposition of stabiliza-tion programs. InTable 2, note is made of three stabilization programs since 1990.9

7 For an excellent survey on this literature seeCarmignani (2003).8 Acemoglu et al. (2003)mention a number of features that create economic instability including:

groups that gain political power try to redistribute economic resources for their own interests bycreating economic turbulences; fighting for power will be greater, since power produces greater gains;and investors may prefer sectors and activities from which they can withdraw their capital quickly.

9 A stabilization program in 2001 attempts to deal with moral hazard problems of deposit guaranteesand bank regulation, reforms in areas of agriculture, pensions and taxation, and the continuing problemof high inflation.


The stabilization program introduced in 1990 was abandoned due to the Gulf Cri-sis in the same year and general elections in 1991. The financial crisis in early1994 leading to the stabilization program introduced in April 1994 was stronglyinfluenced by political decisions.

At the end of 1993, the balance on current account was in deficit (the realexchange rate had appreciated by 22% compared to 1988), the PSBR was upsharply, principal and interest payments on the national debt for the first timeexceeded total tax revenues, and direct advances from CB to the Treasury hadreached new high levels. In January 1994, the government attempted to imposeinterest rate controls and also introduced an income tax on interest income ofgovernment bonds. A down grading of Turkey’s international credit rating bytwo US credit rating agencies in January 1994, provided confirmation that theeconomic environment had taken a turn for the worse. The CB used up most of itsforeign exchange reserves in early 1994 defending the currency. The monthly rateof depreciation in the currency (the Turkish lira/US dollar rate) rise above 16% amonth in February and March 1994 and jumped to 56% in April 1994.

The stabilization program of April 5, 1994 was aimed at ensuring stabilityin the value of the Turkish currency and at increasing exports. To re-establishthe functioning of the bond market, the Treasury issued bonds with an annualcompound interest rate of 406% and taxation of interest earnings was lifted. Tocontain a banking crisis (three small banks werebankrupt) authorities guaranteedbank deposits. To raise revenue new taxes (including a tax on gasoline) wereintroduced, and to establish confidence a stand-by agreement was signed withIMF for the first time in 10 years. The stabilization program of 1994 did succeedin the short term in stabilizing the financial and foreign exchange markets and inreducing the PSBR.10 Although the crisis was past, the fundamental problem ofsubstantial budget deficits was not solved and macroeconomic conditions returnedto pre-crisis period levels. We now turn to estimation of the model.

3. Model and estimation results

3.1. Constant parameter model

To test the hypothesis that the term structure is an unbiased predictor of futureinflation, we employMishkin’s (1990)framework. This model assumes the Fisherhypothesis, rational expectations, and constantex ante real interest rates. Theregression model is given by

�mt − �n

t = �1 + �1(imt − int ) + ε

m,nt (1)

where�mt − �n

t is the change in the futurem-period inflation rate from then-period inflation rate, andimt − int is the interest change, i.e., change in slope of

10 The PSBR was reduced in the remainder of 1994 and in 1995.


the term structure.11 Eq. (1) is obtained by taking the difference of the Fisherhypothesis for two interest rates with maturitiesm andn: imt = rm

t + Et�t+m, andint = rn

t + Et�t+n, respectively. The result

�t+m − �t+n = (rmt − rn

t ) + (imt − int ) + (ut+m − ut+n)

becomesEq. (1) if ex ante real interest rates are constant and expectations arerational. The null hypothesis that the term structure of nominal interest rates is anunbiased predictor of future inflation changes is a test of(�1, �1) = (0, 1). Thefixed coefficient model will now be tested with data for Turkey.

The data consist of monthly observations on inflation rates and one–six-monthrates in the secondary market for government securities for the period of July1991–December 1999. The secondary market for the government securities wasestablished in June 1991, and a comprehensive exchange rate-based stabilizationprogram was put into place in early 2000. The daily interest rates obtained from theIstanbul Stock Exchange are weighted with the transaction volumes to calculatethe interest rates for different maturities.12 The one-month interest rate is definedto have a maturity in the range of 20–40 days, the three-month rate in the range80–100 days, and the six-month rate in the range 160–200 days. Interest rates areexpressed on a compounded base at an annual rate in percent as are in the inflationrates. The inflation rates are measured using consumer price indices published byTurkish State Institute of Statistics.

Table 3shows results of estimatingEq. (1). The generalized method of momentis used, since OLS estimates of standard errors are invalid due to the problem ofoverlapping observations. The estimation results indicate that the null hypothesisof (�, �) = (0, 1) is rejected for all sub-periods and for any maturity. It is ob-served that the statistical significance, the sign and the size of the slope parametershowing the relation between the term structure of interest rates and the changesin inflation are quite sensitive to the periods considered. Estimation of a linearmodel indicates no stable relationship between the term structure of interest ratesand changes in inflation for Turkey during 1991–2000. We now turn to a modelallowing parameters to change over time.

3.2. Time-varying parameter model

We extendMishkin’s (1990)model by assuming the regression coefficients ofthe inflation-change equation are time-varying. We propose a time-varying coef-ficient model with measurement and state equations:13

�mt − �n

t = X′t�t + εt (2)

11 Mishkin (1990)also assumes that the pure expectation hypothesis holds.12 The volume of transactions in the secondary market for securities with longer terms than six

months is virtually non-existent. The government could not sell securities of longer maturity.13 FollowingEngle and Watson (1987), the time-varying coefficients are assumed to follow a random

walk process.


Table 3Constant parameter model: GMM estimation

Variable Model�mt − �n

t = �(m,n),t + �(m,n),t [imt − int ] + ε(m,n),t

(m, n) = (3, 1) (m, n) = (6, 3)

A� 9.4516 (1.3972) 15.6515 (1.8165)� 0.0876 (0.0921) 0.0652 (0.0633)F-test of(�, �) = (0, 1) 105.38 287.18J stat. 0.09 0.13

B� −6.3402 (2.2582) 38.6729 (7.3411)� 1.7019 (0.2006) −0.9393 (0.3694)F-test of (�, � = 0, 1) 75.64 13.96J stat. 0.34 0.36

C� 6.5600 (0.9454) 36.8348 (3.3646)� 0.2649 (0.0607) −0.6678 (0.1207)F-test of(�, �) = (0, 1) 108.22 374.22J stat. 0.18 0.15

A, B and C denote the periods of 1991:07–1999:12, 1991:07–1994:01 and 1995:01–1999:12,respectively. Standard errors are in parentheses.

�t = �t−1 + wt (3)

whereεt ∼ N(0, �2ε ), wt ∼ N(0, Q), X′

t = [1 (imt − int )], �t = [�t �t ], andwt =[ε�t ε�t

]. Q is positive definite 2× 2 matrix,�t and�t represent the time-varyingparameters of the inflation-change equation. Standard Kalman filter technique isused to estimate the system.14

Table 4 reports the maximum likelihood estimation of the inflation-changeequation. A likelihood ratio test is performed to test the null hypothesis of stableregression coefficents. The null hypothesis is rejected at .01 significant level. Themain advantage of the time-varying model compared to the linear model is that thechanges in parameters are determined endogenously and avoid the arbitrarinessinvolved in choosing cut-off lines for sub-sample estimation.15

As a diagonastic test, standardized forecast errors and squares of standardizedforecast errors obtained from the time-varying parameter model are tested forserial correlations. TheQ statistics are reported inTable 4. The results suggest thatthe time-varying parameter models for both(m, n) = (3, 1) and(m, n) = (6, 3)

do not fully explain the dynamics in both the forecast errors and the conditional

14 SeeHamilton (1994)for details of Kalman filter technique.15 Of course, estimation of linear model with the change-points based on some economic and political

events give important insights for conducting economic policies. However, dividing the full sample-period into sub-periods reduces the degrees of freedom, especially when there are many break-points,and lessens the reliability of the estimated values of parameters.


Table 4Time-varying inflation-change equation: MLE estimation


t = �(m,n),t + �(m,n),t [imt − int ] + ε(m,n),t

(m, n) = (3, 1) (m, n) = (6, 3)

�� 4.0306a (0.2824) 4.4494a (0.3451)�� 0.0000 (0.0498) 0.0003 (0.0324)Error Q(12) 51.529 70.410Error Q(24) 84.272 99.050(Error)2 Q(12) 21.641 46.094(Error)2 Q(24) 24.385 47.429H0: �w1 = �w2 = 0 Unrestricted log

likelihood = −266.9973Unrestricted loglikelihood = −269.4823

H1: otherwise Restricted loglikelihood = −298.7639

Restricted loglikelihood = −338.2869

Standard errors are in parentheses.a Indicates significance at 1% level.

variance of the forecast errors. In the next section we consider a more generalmodel that captures endogenous change in the variance of the error term.

3.3. Time-varying parameter model with heteroskedastic disturbances

We now consider a time-varying parameter model that encompasses changingconditional variance due to Markov-switching heteroskedasticity in the disturbanceterm:

�mt − �n

t = X′t�t + εt (4)

where

�t = �t−1 + wt

wt ∼ N(0, Q)

εt ∼ N(0, ht)

ht = �20 + (�2

1 − �20)St, �2

1 > �20

(5)

with

Pr[St = 1| St−1 = 1

] = P11, Pr[St = 0| St−1 = 1

] = 1 − P11

Pr[St = 1| St−1 = 0

] = 1 − P00, Pr[St = 0| St−1 = 0

] = P00

whereX′t = [1 (imt − int )], �t = [�t �t ], andwt = [ε�t ε�t

].Q is positive definite 2× 2 matrix,�t and�t represent the time-varying pa-

rameters of the inflation-change equation.St is an unobserved discrete-value statevariable whose process is determined probabilistically as inHamilton (1988)andKim (1993).16

16 The time-varying parameter model with Markov-switching heteroskedasticity may be seen as analternative to the time-varying parameter model with ARCH disturbance terms developed byEvans


Table 5Time-varying inflation-change equation with Markov-switching heteroskedastic disturbances


t = �(m,n),t + �(m,n),t [imt − tnt ] + ε(m,n),t

(m, n) = (3, 1) (m, n) = (6, 3)

P11 0.8619a (0.0000) 0.6221a (0.0013)P∞ 0.9603a (0.0218) 0.7840a (0.0000)�� 2.4433a (0.2024) 0.7022a (0.0121)�� 0.0001 (0.0843) 0.1140a (0.0029)�0 0.1092 (0.3648) 0.3741a (0.0073)�1 10.1325a (2.0624) 0.4355a (0.0166)Error Q(12) 17.327 20.068Error Q(24) 17.699 22.669(Error)2 Q(12) 3.1715 6.3166(Error)2 Q(24) 3.6051 6.6873Log likelihood −235.0178 −241.0922

Standard errors in parentheses.a Indicates significance at 1% level.

The model inEqs. (4) and (5)allows for endogenous changes both in theparameters and in the variance of the error term. The main advantage of thismodeling strategy is that it allows the unconditional variance of the error term tochange, and modifies the relationship between the term structure of interest ratesand inflation rate changes.

Estimation results of the time-varying parameter model with heteroskedasticdisturbances are reported inTable 5.17 The standard deviation of the time-varyingintercept term inEq. (5) for the model with(m, n) = (3, 1) is statistically sig-nificant. This implies that the difference between the expected real interest ratesat the three- and one-month holding periods is not stable. The standard deviationof the time-varying intercept term inEq. (5) for the model with(m, n) = (6, 3)

is also statistically significant, implying that the difference between the expectedreal interest rates for six and three months is not stable. These findings suggestvolatility in risk premia of bonds in the short term.

In Table 5, the standard deviation of the time-varying slope coefficient inEq. (5)for the model with(m, n) = (3, 1) is not statistically significant. This impliesthat the effect of a change in slope of the term structure, between the three-monthsecurity rate and one-month security rate, on future inflation between one and threemonths in the future doesn’t change over the sample. In contrast, the effect of theterm structure of nominal interest rates on the changes in inflation for the modelwith (m, n) = (6, 3) is found to be time-varying, since�2

� is significantly different

(1991). However, the unconditional variance is constant in the model with ARCH disturbance termswhile it is subject to shifts resulting from endogenous regime changes in the variance structure in themodel with Markov-switching heteroscedasticity.

17 SeeKim (1993) for estimation procedure of the time-varying parameter model with Markov-switching heteroskedastic disturbances.

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0.00

0.20

0.40

0.60

0.80

1.00

1.20

Fig. 1. The smoothed probabilities of state 1 for the model with(m, n) = (3, 1).


from zero. These results imply that the uncertainty associated with economic andpolitical instability becomes more marked as maturity increases.

For the model with(m, n) = (3, 1), the error variance�20 is not statistically

significant and the error variance�21 is statistically significant inTable 5. Error

terms in our model represent the effect of factors other than term structure oninflation changes. The switching probabilities (P00 andP11) for the model with(m, n) = (3, 1) are highly significant and persistent, suggesting that the regimechanges do not occur frequently. The smoothed probabilities of state 1 for thismodel are illustrated inFig. 1and show that there was a change from state 1 onlyduring the first few months of 1994. The time-varying model(m, n) = (3, 1)

with Markov-switching heteroskedasticity captures a switching point in regimethat corresponds to the 1994 financial crisis. The model demonstrates the returnof the economy after the crisis in 1994 to the dominant state of high inflation-highinterest rate parity conditions that prevailed before the crisis.

In Table 5, the variance of the error terms for the model with(m, n) = (6, 3)

are statistically significant. The smoothed probabilities of state 1 for the modelwith (m, n) = (6, 3) are depicted inFig. 2. The severe situation around the timeof the crisis in 1994 is captured by the model, in this the smoothed probabilitiesof state 1 for the model(m, n) = (6, 3) shown inFig. 2 are estimated to be .00in October 1993 and .00 in January 1994. However, the smoothed probabilities ofstate 1 inFig. 2, mostly in the region of about .60, indicate that one cannot identifywhich state the economy operates in during most of the sample period.

For model specification, we test the validity of the heteroskedasticity assump-tion in the disturbance terms. FollowingHamilton (1996), we perform the Waldtest of the null hypothesisP00+P11 = 1 against the alternative ofP00+P11 > 1.The Wald test statistics for the null is

(P00 − (1 − P11))2

var(P00) + var(P11) − 2 cov(P00, P11)∼ �2(1)

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

1992-5

1992-9

1993-1

1993- 5

1993-9

1994-1

1994- 5

1994-9

1995-1

1995- 5

1995-9

1996-1

1996- 5

1996-9

1997-1

1997- 5

1997-9

1998-1

1998- 5

1998-9

1999-1

1999- 5

1999-9

Fig. 2. The smoothed probabilities of state 1 for the model with(m, n) = (6, 3).


The Wald test statisitics are calculated 5.68 for the model with(m, n) = (3, 1)

and 23.19 for the model with(m, n) = (6, 3), indicating no persistence is left afterthe effects of Markov-switching heteroskedasticity on disturbance terms are takeninto account. Secondly,Q-statistics for both the standardized forecast errors andthe standardized squared forecast errors show no significant serial correlations inthe models considered. Thus, the specification test results suggest that the model oftime-varying parameters with Markov-switching provides a good characterizationof the inflation-change equations.

4. Policy implications and conclusion

In this paper we investigate the relationship between the term structure of in-terest rates and changes in inflation for the Turkish economy during 1990–2000,a period of high inflation, high budget deficits, and political instability. Constantparameter and time-varying parameter models are rejected by the data. We findthat a time-varying parameter model with Markov-switching heteroskedastic dis-turbances provides a reasonable explanation of the relation between the term struc-ture of interest rates and changes in inflation. Political instability and consequentfrequent change in monetary and fiscal policies and stabilization regimes duringthe period make allowance for endogenous parameter and regime change attractivefor study of the Turkish economy.

The intercept coefficient in the relationship between change in inflation and termstructure of interest rates is found to be time-varying, implying that expected realinterest rates and risk premia between maturities vary over time. However, for theone–three-month range, predictions from changes in slope of yield curve for infla-tion (the slope coefficient) is not time-varying (in contrast to the slope coefficientfor longer maturities). This result is consistent with the time-varying parametermodel with Markov-switching heteroskedasticity for the one–three-month hori-zon, indicating a change from the dominant state of high inflation-high interest rateparity conditions only for a few months corresponding to the 1994 financial crisis.

Our findings imply that the term structure of interest rates is limited as a sourceof information for future inflation, especially at longer horizons, in an economysubject to regime changes such as that of Turkey. The model implies regime changeat times consistent with dates of substantial economic and political uncertainty inTurkey. It is likely that stability, in the sense of time-invariant parameters andunchanging variance of error terms, can be achieved only by reducing inflationthrough circumscribing substantial government budget deficits and the politicalinstability underlying them. Several stabilization programs have addressed theproblem of high inflation in Turkey over the years, yet all have failed in reducinginflation to acceptable rates. To achieve stability Turkey requires implementationof credible structural reform of the tax and expenditure systems to eliminate thepublic sector borrowing requirement, and of the legal and political systems toensure that successive governments will not continue to pursue policies that are


dynamically consistent with current institutions but are sub-optimal for societywelfare.

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